Local Popularity and Time in top-N Recommendation-Reference-Cited by-同舟云学术

Local Popularity and Time in top-N Recommendation

Published:2019 Issue: Volume: Page:861-868
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Anelli Vito Walter,Di Noia Tommaso,Di Sciascio Eugenio,Ragone Azzurra,Trotta Joseph

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-15712-8_63

Reference25 articles.

1. Lecture Notes in Computer Science;G Adomavicius,2001

2. Adomavicius, G., Tuzhilin, A.: Context-aware recommender systems. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 217–253. Springer, Boston, MA (2011). https://doi.org/10.1007/978-0-387-85820-3_7

3. Anelli, V., Di Noia, T., Di Sciascio, E., Lops, P.: Feature factorization for top-n recommendation: from item rating to features relevance. In: Proceedings of RecSysKTL, pp. 16–21 (2017)

4. Bao, H., Li, Q., Liao, S.S., Song, S., Gao, H.: A new temporal and social PMF-based method to predict users’ interests in micro-blogging. Decis. Support Syst. 55(3), 698–709 (2013)

5. Bellogín, A., Sánchez, P.: Revisiting neighbourhood-based recommenders for temporal scenarios. In: Proceedings of TempRec, pp. 40–44 (2017)

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Capturing Popularity Trends: A Simplistic Non-Personalized Approach for Enhanced Item Recommendation;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

2. User Popularity Preference Aware Sequential Recommendation;Computational Science – ICCS 2023;2023

3. Hybrid Weighted Retrieval of Twitter Users for Temporally Relevant Full-Text Querying in the Media Industry;2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter);2022-12

4. Interactive POI Recommendation: applying a Multi-Armed Bandit framework to characterise and create new models for this scenario;Brazilian Symposium on Multimedia and Web;2022-11-07

5. A bias detection tree approach for detecting disparities in a recommendation model’s errors;User Modeling and User-Adapted Interaction;2022-07-11